Entity resolution involves identifying two or more records (or fields associated with the records) that are associated with the same entity, or person, and consolidating the respective records into a single record. When dealing with different sources for the records, the algorithms have to resolve the discrepancies between the sources of the records. For example, the field names and formats may be different between different sources. Entity resolution algorithms typically rely on user-defined functions that compare fields or records to determine if they match (e.g., are they likely to represent the same real-world person). When a match is found, the matching records or fields are typically combined into a single record. Often, when the records are combined, the associated fields may be combined as well and data may be lost (e.g., creating a new name based on two slightly different versions of the name in the two matched records).